Economic Implications With Newer Agents to Reduce Cardiovascular Risk in Diabetes

Am J Manag Care. 2018;24:-S0

Extra Healthcare Costs Associated With Cardiovascular Disease

Cardiovascular disease (CVD) plays a significant role in the morbidity and mortality in type 2 diabetes (T2D). In addition to the negative impact on the health of patients, people with T2D and CVD encounter higher total healthcare costs compared with patients with T2D and without CVD. The FDA guidance of 2008 recommending cardiovascular outcomes trials (CVOTs) for T2D drug candidates prompted pharmaceutical companies to conduct such studies. Some of those drug candidates appear to have beneficial physiologic effects on cardiovascular outcomes. Pharmacoeconomic analysis can correlate observed improvements to cardiovascular outcomes to savings in healthcare spending and assist health plans in assessing the value of diabetes medications. To date, most pharmacoeconomic studies for antihyperglycemic drugs have been conducted using surrogate markers of CVD risk (eg, glycated hemoglobin, systolic blood pressure, body mass index, plasma lipid levels) and have established the economic benefit and value of diabetes drugs based on reduction in cardiovascular events. A few analyses have been conducted based on CVOT efficacy data and similarly demonstrate value in patients at high CVD risk. Combined, the pharmacoeconomic data reinforce that newer agents with CVOT benefit represent good value in general, as well as for patients with high CVD risk, and support managed care decisions regarding treatment coverage and recommendations for newer diabetes agents.

The substantial economic impact of diabetes is difficult to overstate. For 2017, the American Diabetes Association (ADA) estimated that the total costs associated with diagnosed diabetes was $327 billion in the United States, with the distribution of indirect and direct costs generally about 30% ($90 billion) and 70% ($237 billion) respectively.^1,2 Diabetes-related costs have increased 26% from 2012, which is attributed to growths in prevalence and medical costs.¹ This growth trend is expected to continue, with total costs of diabetes estimated to exceed a half trillion dollars (≈$622 billion) in 2030 due in large part to increasing prevalence.^2,3

Individuals with diabetes have costs that are over 2 times higher than for those without diabetes.¹ These incremental costs are associated with comorbidities and diabetes complications, with the costs of comorbidities accounting for a large portion of direct medical costs of diabetes.^2,4 A closer look reveals that cardiovascular disease (CVD) is a major driver of the direct medical costs of diabetes comorbidities, and these direct medical costs manifest in multiple ways. Diabetes also contributes to 16% of the total deaths due to CVD, which, in addition to the personal loss, results in $7.6 billion in lost productivity.¹

A retrospective study by Mehta and colleagues provides additional insights into the role of CVD as a cost driver specifically in type 2 diabetes (T2D), which accounts for 90% to 95% of all cases of diabetes.⁵ Using a claims database linked with electronic medical records, Mehta et al analyzed the incremental costs of CVD in patients with T2D 18 years or older for the years 2011 to 2013.⁶ Patients with T2D and a history of CVD had per-patient per-month healthcare costs that were 16% ($200) higher than costs for patients without CVD history when adjusted for demographics and other comorbidities (rate ratio [RR], 1.16; 95% CI, 1.13-1.19; P < .0001).⁶ Similar statistically significant higher healthcare costs were also observed for outpatient visits, emergency department visits, inpatient hospital visits, and prescription drugs.⁶

The study also revealed greater disparities in total healthcare costs between cohorts with or without CVD based on certain demographic subgroups. When compared with people without a history of CVD, total healthcare costs increased by 56% in the cohort aged younger than 45 years, by 27% in the cohort aged 45 years to 64 years, but by just 2% in the cohort aged 65 years or older. The increase in healthcare costs in men with CVD history was 14%; in women with CVD history the increase was 19%. Furthermore, racial differences were evident as the observed increases in healthcare costs with CVD history were 5%, 11%, 22%, and 33% for Asians, whites, Hispanics, and African Americans, respectively (Table 1).⁶

In a broader study of adults (>17 years old) for the time period of 2002 to 2011 using the Medical Expenditure Panel Survey Household Component, Ozieh et al determined that the incremental costs associated with CVD in patients with diabetes was $3374 (95% CI, $3068-$3679; P < .01).⁷ In addition, patients with diabetes experienced significantly greater costs in each category of medical expenditures evaluated (total medical, hospital inpatient, prescription medical, office-based, home health, and emergency department). Compared with patients without diabetes, healthcare expenditures were more than 2 times greater for total healthcare costs, 1.9 times greater for office visit costs, 2.6 times greater for hospital inpatient costs, and 3.4 times greater for prescription drug costs compared with people without diabetes.⁷ The data highlight the significant economic impacts of CVD on healthcare costs associated with diabetes.

With 10 years of experience since the FDA guidance mandating evaluation of cardiovascular risk for new antihyperglycemic drugs, researchers have engaged in healthy discussions on their merits and on the merits of cardiovascular outcomes trials (CVOTs), including how to determine the costs and benefits of such large-scale trials, how to improve study design, and how to translate the knowledge gained into clinical recommendations.^8-12 Through this process, researchers have demonstrated that newer diabetes agents do not impart cardiovascular risk. In fact, select sodium-glucose cotransporter 2 inhibitors (SGLT2is) (empagliflozin and canagliflozin) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) (liraglutide, semaglutide) have been shown to reduce the risk of major adverse cardiovascular events (MACEs) in high-risk patients. For payers, these data should contribute to the value assessment of these newer diabetes medications.

Evaluating the Pharmacoeconomics of Antihyperglycemic Drugs

While this activity focuses on the economic implications of newer diabetes drugs vis a vis the reduction of cardiovascular events, clinicians should always be mindful of the health and economic benefits of lifestyle modifications and appropriate pharmacologic treatment of CVD risk factors, such as hypertension and dyslipidemia.^13-17 However, as it is a chronic and progressive disease, patients with diabetes require pharmacologic interventions to manage hyperglycemia and reduce the risk of both CVD and microvascular complications. Evaluating the pharmacoeconomic efficacy alongside the pharmacologic efficacy is critical to support diabetes treatment decisions made by payers, providers, and patients.

Cost-Effectiveness of Diabetes Drugs: Cardiovascular Outcomes

Studies that evaluate the overall cost-effectiveness of diabetes drugs are relatively common. The question of interest here is the economic impact of diabetes drugs based on reductions in CVD risk and/or cardiovascular outcomes. Given that CVOT data are relatively new, pharmacoeconomic studies using CVOT data are limited and to date have been published for pioglitazone, which is a thiazolidinedione, and empagliflozin, an SGLT2i. Based on the prospective pioglitazone clinical trial in macrovascular events (PROactive) study, the cost-effectiveness of pioglitazone was compared with placebo. The PROactive study involved more than 5000 patients with T2D with high CVD risk in a prospective, double-blind, randomized, parallel group clinical trial that was conducted in multiple international sites and followed patients for a median of 34.5 months.¹⁸ Patients received either pioglitazone or placebo in addition to their existing diabetes treatments and were treated to a glycated hemoglobin (A1C) goal of less than 6.5%. A1C reduction from baseline was statistically significantly greater with pioglitazone than placebo groups (−0.85% and −0.3%, respectively; P < .001), although, on average, the cohorts did not achieve the less than 6.5% goal. Although, the study did not find a significant reduction in the risk of the primary end point (all-cause mortality plus nonfatal myocardial infarction [MI], silent MI, acute coronary syndrome, and stroke, as well as endovascular or surgical intervention in the coronary or leg arteries, amputation above the ankle) (hazard ratio [HR], 0.90; 95% CI, 0.80-1.02; P = .095) a reduction in CVD risk per the main secondary end point (all-cause mortality, nonfatal MI, and stroke) was identified (HR, 0.84; 95% CI, 0.72-0.98; P = .027).

The cost-effectiveness of pioglitazone was determined for both the United Kingdom and the United States.^19,20 Both analyses, conducted from a payer perspective, were based on the PROactive study population and event rates for the components of the primary composite end point. They used a version of the IMS (now IQVIA) CORE diabetes model that was modified to incorporate observed reductions in cardiovascular events, including heart failure (HF) hospitalizations, and edema, that also retained microvascular outcomes. The model projected the incremental cost-effectiveness ratio (ICER), quality-adjusted life expectancy (QALE), and quality-adjusted life-years (QALYs). In the UK study, the cost-effectiveness was determined for 2 time frames: short-term (within-trial) and long-term (35-year horizon). For the within-trial analysis, pioglitazone increased QALE by 0.0190 QALY compared with placebo, with an increased cost of £102 ($135.01 USD) per patient, which translated to an ICER of £5396 ($7146.08 USD) per QALY.¹⁹ When modeled for a 35-year time frame, pioglitazone increased QALE by 0.152 QALYs compared with placebo, with an increased cost of £619 ($819.76 USD) per patient and a calculated ICER of £4060 ($5376.77 USD) per QALY.¹⁹ The US analysis focused on a lifetime horizon of 35 years. Like the UK study, pioglitazone increased QALE by 0.166 QALYs compared with placebo. Treatment with pioglitazone increased a patient’s lifetime total direct costs by $7305, and the ICER for pioglitazone compared with placebo was $44,105 per QALY.²⁰ Both studies found pioglitazone to be cost-effective in the respective countries of analysis.^19,20 Sensitivity analyses indicated that ICERs were most sensitive to time horizon, which reflects the long-term nature of the benefits of CVD risk reduction.^19,20 Application of these findings must be used cautiously given that risk reduction per the PROactive primary end point did not reach significance.

The 2 recently published pharmacoeconomic analyses of empagliflozin were based on data from the Empagliflozin Cardiovascular Outcome Event Trial in Type 2 Diabetes Mellitus Patients—Removing Excess Glucose (EMPA-REG OUTCOME) trial with Greece as the country of analysis and the US analysis data added from other published epidemiologic studies.^21,22 The EMPA-REG OUTCOME trial was designed as a noninferiority study to assess the effect of empagliflozin (10 mg or 25 mg) versus placebo on the primary composite 3-point major adverse cardiovascular event (3P-MACE) outcome of death from cardiovascular causes, as well as nonfatal MI or stroke in patients at high cardiovascular risk.²³ More than 7000 patients were treated in the EMPA-REG OUTCOME trial in a randomized, double-blind, placebo-controlled study that was conducted at multiple international sites and had a median follow-up time of 3 years.²⁴ In this study, the placebo-adjusted change in A1C was modest (−0.3%) per study design. Empagliflozin-treated patients were significantly less likely to experience a MACE (HR, 0.86; 95.02% CI, 0.74-0.99; P < .001 for noninferiority; P = .04 for superiority for 3P-MACE composite outcome).

The pharmacoeconomic study with Greece as the country of analysis was based on a simulation model conducted from a payer perspective over a lifetime horizon for the high-risk EMPA-REG cohort. The model included components of the primary end point plus unstable angina, HF hospitalization, cardiovascular death, transient ischemic attack, revascularization, macroalbuminuria, and acute renal injury. Empagliflozin was estimated to increase mean survival by 2.13 life-years (LYs) compared with standard of care and increased QALYs by 0.91 at an increased cost of €4235 ($4955.77 USD) for a calculated ICER of €4633 ($5421.51 USD) per QALY.²¹ In a probability sensitivity analysis (PSA), the authors found that empagliflozin had a 100% probability of being cost-effective at a willingness to pay (WTP) threshold of €34,000 ($39,786.60 USD). The model was robust to shorter time horizons of 5 years and 10 years, but not at 3 years, which was the duration approximating the EMPA-REG median follow-up time.

A second empagliflozin study based on EMPA-REG data from a US payer perspective over a lifetime horizon used a Markov model that included CVD and end-stage renal disease as defined disease states but did not include retinopathy or neuropathy. The model predicted that empagliflozin was associated with a $98,484 increase in total lifetime treatment costs coupled with a 1.293 increase in QALYs for an ICER of $76,167 per QALY compared with standard of care.²² As with the Greece study, this model was sensitive to time horizon, with ICER increasing to $406,258 with a 3-year time horizon. In a Monte Carlo simulation, 96% of the simulations found empagliflozin to be cost-effective at a WTP threshold of $100,000. While there is no set WTP threshold in the United States, some experts suggest that a threshold of $100,000 to $150,000 is appropriate for many analyses.²⁵ Thus, in both settings of the United States and Greece, the authors concluded that empagliflozin was cost-effective in patients with high CVD risk, based on country-specific costs and WTP thresholds.^21,22

Cost-Effectiveness Based on Intermediate Outcomes

More commonly, pharmacoeconomic studies have estimated the cost-effectiveness of diabetes drugs by modeling diabetes outcomes, including CVD outcomes, through intermediate measures of efficacy (ie, reduction in A1C, blood pressure, lipids, and/or body weight). These models are based on inputs from applicable clinical trials conducted in a more general diabetes population (ie, not limited to those with high CVD risk) with a primary study outcome of improvement in glycemic control. Researchers used validated pharmacoeconomic models to compare the relative effects of different drugs.

Lee and colleagues used the CORE Diabetes Model to estimate the long-term cost-effectiveness of liraglutide versus sitagliptin using data from the 1860-LIRA-DPP-4 52-week trial.²⁶ They modeled 3 treatments: liraglutide 1.2 mg daily, liraglutide 1.8 mg daily, or sitagliptin 100 mg daily, each in combination with metformin. Treatment continued for 5 years of the model after which all patients were switched to basal insulin therapy for the completion of the 35-year simulation. Authors used a conservative WTP threshold of $50,000 per QALY. The 35-year ICERs for liraglutide compared with sitagliptin were estimated to be $25,742 per QALY gained and $37,234 per QALY gained for liraglutide 1.2 mg and 1.8 mg, respectively.²⁶ Except for the 10-year simulations for both liraglutide doses and the 20-year simulation for liraglutide 1.8 mg, all other ICERs were estimated to be below the $50,000 per QALY WTP threshold.²⁶

In another study with liraglutide (dosed at 1.2 mg or 1.8 mg), Davies et al used the CORE Diabetes Model to compare the drug’s cost-effectiveness to glimepiride or sitagliptin as add-on to metformin using efficacy data from the LEAD-2 study and the 1860-LIRA-DPP-4 trial and a lifetime horizon.²⁷ The ICERs for liraglutide doses were estimated to be £9449 ($12,513.60 USD) and £16,501 ($21,852.70 USD) per QALY gained versus glimepiride, and £9851 ($13,046 USD) and £10,465 ($13,859.10 USD) per QALY gained versus sitagliptin for the 1.2 mg and 1.8 mg doses, respectively.²⁷

Using the CORE Diabetes Model Version 8.5+, Barnett et al recently published another analysis of liraglutide 1.8 mg compared with sitagliptin 100 mg based on LIRA-SWITCH trial data over a lifetime horizon.²⁸ Treatment with liraglutide was projected to increase QALY from 9.02 for sitagliptin to 9.18 for liraglutide and increase overall costs from £22,362 ($29,614.60 USD) for sitagliptin to £24,737 ($32,759.90 USD) for liraglutide. The estimated ICER of £15,423 ($20,425.10 USD) per QALY gained was deemed to be cost-effective for use in the United Kingdom.²⁸

Analyzing pioglitazone as a first-line treatment in Canada, Coyle et al used clinical data from the United Kingdom Prospective Diabetes Study (UKPDS) and a Markov model to estimate health outcomes and economic impact for patients with T2D in comparison to other first-line therapies including glyburide, metformin, and diet and exercise over a lifetime horizon.²⁹ Their analysis projected that pioglitazone treatment would increase discounted life expectancy by 0.13 to 0.35 LYs compared with the other first-line treatments. The discounted incremental costs per LY gained for pioglitazone treatment were $54,000 (CAD) versus metformin; $42,000 (CAD) versus glibenclamide; and $27,000 (CAD) versus diet and exercise.²⁹

By using surrogate outcomes, the studies outlined provide guidance on the cost-effectiveness of different pharmacologic treatments in a more general diabetes population, considering the effect of improved glycemic control on both macrovascular and microvascular complications. Modeling pharmacoeconomic data by extrapolating short-term surrogate outcomes over a long-term time horizon may be helpful in evaluating the cost-effectiveness of drugs in the absence of cardiovascular outcomes. However, the limitation in this approach, assuming risk reduction is due to improvement in surrogate end points (eg, A1C, body mass index [BMI], blood pressure, lipids) versus observed risk reduction from trials, must be recognized by those evaluating the published data when making clinical decisions. Table 2 summarizes the important aspects of the pharmacoeconomic studies cited, including the types of outcomes evaluated (cardiovascular outcomes or intermediate outcomes) and base case ICERs.^19-22,26-29

Future Directions in Pharmacoeconomic Analysis

Managing CVD risk in patients with T2D will continue to be critical for health and economic outcomes. Newer drug classes, such as SGLT2is and GLP-1 RAs, provide good glycemic response with the added benefits of weight loss and modest systolic blood pressure reductions. Several CVOTs are nearing completion in the next few years.¹¹ Researchers will have the opportunity to evaluate the data in pharmacoeconomic models based on observed cardiovascular outcomes, which account for CVD risk reduction due to mechanisms beyond improvements in CVD risk factors, such as hyperglycemia, obesity, hypertension, and dyslipidemias.

Likewise, observational studies in the real-world setting will also provide economic outcomes data as observed with CVD risk reduction in broader populations, as well as provide alternative data input for pharmacoeconomic modeling. Such studies have shown significant reductions in A1C and/or body weight with SGLT2i and GLP-1 RA therapy.^30-32 Expanding the concept of studying a broad population in the real world, the Comparative Effectiveness of Cardiovascular Outcomes (CVD-REAL) trial is investigating cardiovascular outcomes in a multinational, observational study of more than 300,000 patients.³³ A subset analysis of CVD-REAL observed that SGLT2i treatment was associated with lower risks of MI and stroke compared with other glucose-lowering drugs (MI: HR, 0.85; 95% CI, 0.72-1.00; P = .05; stroke: HR, 0.83; 95% CI, 0.71-0.97; P = .02).³⁴

Potential Opportunities to Drive Down Costs, Morbidity, and Mortality of T2D

Diabetes independently contributes to the risk of developing CVD, with common comorbidities of hypertension and dyslipidemia adding to the risk. While recent improvements in CVD morbidity and mortality are encouraging, CVD remains the foremost cause of morbidity and mortality in patients with diabetes. In addition, CVD is a major driver of diabetes costs (direct and indirect).¹ CVOT data are helping to more comprehensively establish the safety and benefit of newer diabetes therapy in reducing CVD risk. In addition, pharmacoeconomic evaluations based on CVOT data are starting to emerge and reinforce the cost-effectiveness of these agents versus standard of care in patients with high CVD risk.

When using ICERS to analyze pioglitazone and empagliflozin with CVOT data, the studies presented suggest that the drugs are cost-effective compared with the QALY thresholds for each respective country of analysis. The cost-effectiveness tended to become evident or more pronounced at longer time horizons as impact of CVD risk reductions is more fully realized across the population.^19-22

There are numerous aspects of the CVOT designs that, while important for feasibly assessing cardiovascular outcomes, introduce limitations for using CVOT data in economic evaluations. These trial design factors include using an event-driven design over a relatively short period of time in patients with high CVD risk.¹¹ This approach may underestimate beneficial cardiovascular effects of these drugs over a longer period of time and may also fail to identify longer term risks that emerge. Further, CVOTs for SGLT2is and GLP-1 RAs attempted to achieve comparable glycemic control between groups, thereby attempting to remove the effects of glycemic control on cardiovascular outcomes. Thus, the CVOT data for these newer classes help to isolate cardioprotective benefits, but the generalizability of findings is currently limited in terms of both patient population that may benefit and the overall effects of treatment. Thus, pharmacoeconomic studies based on CVOT data are also limited to a high-risk population and do not fully reflect the economic aspects of treatment.

The pioglitazone CVOT—PROactive&mdash;generally has the same set of limitations. PROactive was based on a high-risk population with a short follow-up time. However, A1C reduction was both statistically and clinically significantly greater in the pioglitazone group than in the placebo group. Pharmacoeconomic analyses for lifetime models based on PROactive data used a modified CORE model, which incorporated microvascular outcomes, including HF outcomes, while retaining microvascular outcomes. Thus, these pharmacoeconomic assessments may provide a more comprehensive account of pioglitazone treatment benefits and risks in the study population. Overall, the pharmacoeconomic assessments of pioglitazone (including the assessment using surrogate markers) suggest that the drug is cost-effective, particularly in younger patients and with longer time horizons.^19,20,29 The pioglitazone pharmacoeconomic studies were conducted before the generic availability of pio-glitazone in the United States, thus ICERs based on the generic price would obviously be more favorable, assuming all other parameters remain the same. On the other hand, PROactive failed to attain statistical significance for the primary study end point, a limitation that must be considered when assessing the applicability of findings.

Similar to the pharmacoeconomic analyses of pioglitazone and empagliflozin using CVOT data, liraglutide was generally considered cost-effective when using surrogate CVD markers (eg, A1C, BMI, lipid levels).^26-28 Analyses based on direct cardiovascular outcomes should provide more comprehensive pharmacoeconomic data for evaluating liraglutide and other T2D drugs.

Implications for Managed Care

The emerging CVOT data help to establish cardiovascular safety with newer diabetes medications, and several CVOTs provide evidence that newer agents are also cardioprotective, leading to reduction in CVD risk that may go beyond what is expected from improved glycemic control. The benefits of these innovative therapies over standard of care also come with a higher price, thus managed care decision makers must decide if these agents represent good value.

Existing pharmacoeconomic data for SGLT2is and GLP-1 RAs have demonstrated cost-effectiveness based on models that estimate microvascular and CVD risk reduction based on improvement in intermediary markers of risk, primarily A1C, blood pressure, and body weight. These studies are more reflective of the general T2D population and often provide cost-effectiveness relative to other active comparators.

CVOT-based pharmacoeconomic data are also starting to evolve. However, the nuances of the CVOT designs must be taken into consideration, namely their generalizability to a managed care organization’s overall diabetes population and the scope of risks and benefits assessed. As such, the pharmacoeconomic studies based on CVOT data should be used to augment rather than replace existing pharmacoeconomic data.

Given the totality of clinical and economic evidence, agents demonstrating improvement in cardiovascular outcomes represent preferable second- and/or third-line options versus other classes that have not shown to have cardiovascular benefits. This approach is consistent with current treatment guidelines, such as the 2018 ADA Standards of Medical Care in Diabetes, which recommend use of agents with demonstrated CVD risk reduction in patients with established CVD after first-line metformin.³⁵ Of agents with demonstrated cardiovascular benefit, pioglitazone is available as a generic but is also associated with considerably higher risk of serious HF. Thus, use of pioglitazone may not be appropriate for many patients at high CVD risk. This leaves the SGLT2i (empagliflozin and canagliflozin) and GLP-1 RA (liraglutide and semaglutide) agents, which do not have HF risk. Selection of treatment between these agents should then be based on patient factors and preferences as related to product differences in adverse effects, administration (eg, weight loss goals, tolerance of gastrointestinal adverse effects, oral versus injectable, renal function, risk for amputation), and patient costs.

Conclusions

Given the burden of CVD in diabetes, the CVOT data are helping to establish the safety and benefit of newer diabetes therapy in overall diabetes care, specifically their role in reducing CVD risk. In addition, pharmacoeconomic evaluations based on CVOT data reinforce that these newer agents represent good value for payers, as well as for patients with high CVD risk. Combined, the clinical and economic data can support managed care decisions regarding treatment coverage and recommendations for newer diabetes agents, particularly in prioritizing second- and third-line diabetes treatments for high-risk patients to avoid undesirable cardiovascular outcomesAuthor affiliation: Associate Professor and Director, Pharmaceutical Evaluation and Policy Division, University of Arkansas for Medical Sciences, College of Pharmacy, Little Rock, AR.

Funding source: This activity is supported by an independent educational grant from Boehringer Ingelheim Pharmaceuticals, Inc. and Lilly USA, LLC.

Author disclosure: Dr McAdam-Marx has the following relevant financial relationships with commercial interests to disclose:

GRANTS/RESEARCH SUPPORT — Sanofi-Aventis

STOCK/SHAREHOLDER — GlaxoSmithKline

Authorship information: Concept and design, analysis and interpretation of data, and critical revision of the manuscript for important intellectual content.

Address correspondence to: cmcadammarx@uams.edu.

Medical writing and editorial support provided by: Thomas J. Cook, PhD, RPh.

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